Ask the Experts: Will Artificial Intelligence Affect SEO?

The topic of artificial intelligence is one that has been growing in popularity recently. Both businesses and consumers are loving the advancements and engaging with AI on a regular basis. 32% of executives say voice recognition is the most-widely used AI technology in their business.

The reality of AI shows how far and fast our technology is advancing. By 2018, six billion connected devices will proactively ask for support, whether you want it or not. That means the opportunity to have your questions answered immediately will be incredibly available and in a means that it hasn’t been before.

How AI will shape our future we aren’t a hundred percent sure yet. We do know that people are engaging with it though, and at a growing rate.

Gartner estimates that by 2020, 85% of customer interactions will be managed without a human. As terrifying as that may sound to us humans, we also need to consider the impact AI will have on search and to SEO’s.

With all of the hype and new stats about AI, I had to reach out to the experts and see what SEO’s have to say about how this may affect search in the long run.

Let’s see what they had to say...

Defining Artificial Intelligence and Machine Learning

by JP Sherman

First, I want to describe the subtle differences between artificial intelligence and machine learning.

Artificial intelligence is a high level concept that describes the ability of machines to do two primary things: independently perform tasks and make decisions based on the data it has and to synthesize data to make a unique decision based on that input.

Driverless cars are a very practical application of AI in action in the real world. A more search-focused action of AI is Google’s RankBrain processing signals from a site or page to create a unique ranking factor set that can satisfy the intent of the user.

Machine learning is the application of an AI rule-set to allow machines to consume data and learn for themselves. A good example of this is how Google understands entities. For example, Google understands that Batman is an entity. This entity is associated with locations, enemies and allies.

Once the machine knows that Batman is associated with these categorizations, it is programmed to find entries that fit those categories. The machine searches for “locations” and comes up with “Batcave”, “Gotham City” and “Arkham Asylum”. Its search for enemies comes up with “Joker”, “Two-Face” and “Bane”.

The machine is building a template to understand the relationships between Batman and other entities. As the machine starts to collect data on associations and relationships, it can use the template it built for Batman to start filling in data on other entities.

The critical thing to understand is that AI is the set of rules that perform intelligent tasks independently and machine learning is the application of those rules.

So, how do we, as search professionals, apply artificial intelligence and machine learning to influence ranking and deliver what users intend to the SERP?

The most accessible way for us to influence results is to use structured markup, powered by a robust taxonomy. The good news is that most CMSs have a way to natively build a taxonomy. Think of taxonomies as a way to define a “thing”: a product type, a content type or any other high level category.

Building a taxonomy will create a unique definition that lists the unique attributes of what you’re defining. I highly recommend having a working knowledge of the Dublin Core Metadata Initiative.

Once you’ve built a good taxonomy that defines things, use that data to build structured markup schema, using attributes from Schema.org.

I know that I’m one of those people who bang on the “structured markup” drum but the advances in AI and ML will primarily affect the organizations that are structuring and defining the data they have in the format that the machines can consume easily.

This is the point where I step away from search engine optimization and point to digital assistants like the Amazon Echo, IBM’s Watson and a host of other non-search engines that consume web data to understand entities and relationships in order to synthesize information.

Structuring your data cannot be viewed with just the perspective that it’ll give you a greater position on Google’s SERP, it needs to be viewed with the idea that, if done well, your data can reach and influence a greater audience than ever as machine learning expands into your home, your car and many other invisible areas of your life.

JP Sherman is a ten+ year veteran of Search, Findability and Competitive Intelligence. JP works as the Search & Findability Manager for the Red Hat Customer Portal. His responsibility is to bridge the intention gap between hundreds of thousands of technical and support documents and the customers looking for them in Google and Red Hat’s internal search platform.

Will AI Affect SEO? Yes, But Only Shitty SEO

by Ryan Jones

AI is just more support that we need to stop thinking of SEO as gaming an algorithm and evolve to serving the user. AI will make it harder for those intent on “tricking” or “gaming” the algorithms to rank – but it shouldn’t have an effect on those doing real marketing. SEO has become real marketing and some people missed the transition.

Whether it’s an algorithm or AI, the goal is to surface sites that help the users perform whatever task is at hand. If your’e focusing on keyword density, pagerank, or TF-IDF, then yeah AI might pose some problems for you.

If you’re attempting to understand the competition, the marketplace, the searcher, the reasons why they search, and then create content that fills a need in the market while catering to the searcher’s intent – and do so in a way that’s indexable and understandable, you’ll survive AI and whatever comes after it.

Ryan Jones is an SEO Director at SapientRazorfish where he manages an international team working on large fortune 500 clients. In his spare time he runs WTFSEO.com, plays hockey, and writes bios about himself in the third person.

How Virtual Assistants Can Effect Rankings

by John Leo Weber

AI stands to have the biggest affect on how we use search in the area of virtual assistants and voice search technology like Google Home, Apple’s Siri, or Amazon Alexa. When search comes off of the desktop screen and into voice search, we lose the need for 10 search results and a ranking algorithm to show us so many options.

With the new voice search algorithms, we will have a zero sum system where there is one answer to a question and every other answer becomes irrelevant.

For example, you might ask your virtual assistant technology: “Who is the best cosmetic dentist near me?” Then, the assistant will reply “I found a cosmetic dentist with 5 star reviews one mile away — would you like me to schedule you an appointment?”

With this example, there is no need for the number 2-10 search results! There is one result and the virtual assistant can contact the business for you. “Rankings” as we know it will be a thing of the past.

It will be up to search marketers to understand the new “voice algorithms” so that we can figure out how to get our clients in front these new searchers. Mobile now accounts for over 50% of Google searches, and the use of voice search is increasing to boot. It’s time for SEOs to start thinking beyond Google rankings and into the future of search algorithms with voice search.

John Leo Weber is the COO at Geek Powered Studios, a full service digital marketing agency in Austin, TX. John helps to craft the digital strategy for all Geek Powered clients and writes about marketing for a variety of publications across the web.

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About Ashley Ward

Ashley Ward is a Corporate Speaker for SEMrush, an EPIC all-in-one tool designed to make life simpler for digital marketers.
Ashley is passionate about helping businesses and individuals gain longterm ROI through teaching content marketing and social media tactics.
With over 6 years in the digital marketing industry, Ashley brings first hand experience and case studies to inspire marketers around the world to better their strategies using the SEMrush platform and unique marketing tactics.
She regularly speaks at workshops and conferences like Pubcon, RetailGlobal, SMS, and more. Ashley is also a contributing writer to industry blogs such as Search Engine Journal and AuthorityLabs.

The coolest example of how structured data is making giant changes today is Google for Jobs. What’s best is how Google is making the carrot really sweet this time, making the structured data count more than ever. It’s job search interface is next-generation compared to the job board giants, making browsing jobs orders of magnitude more user friendly. Beyond that, in the actual results, you can see some AI decisions being made based on structured data when you get really specific, as a user, with job search terms.

The other thing that’s really awesome about AI taking more of a role in search results, with or without structured data to work with is this: If I let a SME generate two pages of content in their own words things will be different than they are now. The future potential of it getting ranked is going to be a lot better than that same content’s potential in the past. SEO won’t be able to be gamed as easy, but that’s not bad for SEO experts, it’s actually good! You won’t have to revise your SME’s syntax as rigorously, and the relevance of the inbound links will matter so much more. That’s where we see the majority of the gaming going on now because the Page Rank algorithm has a long way to go. Page Rank will still be the foundation, but the connections will be weighted better, yet another layer of algorithm to make the search engineer’s job easier and capable of doing more.

I truly think only time will tell, Filip. People are still warming up to the idea of AI and the use of it will only grow with time, which means white hat SEO will need to adapt even more to voice search.